Achievable Stereo Vision Depth Accuracy with Changing Camera Baseline

J. Sasiadek, M. Walker
{"title":"Achievable Stereo Vision Depth Accuracy with Changing Camera Baseline","authors":"J. Sasiadek, M. Walker","doi":"10.1109/MMAR.2019.8864723","DOIUrl":null,"url":null,"abstract":"This paper examines the effect on achievable depth accuracy of a stereo vision system as the baseline between the two camera sensors changes. This is critical for Unmanned Aerial Vehicle navigation or UAV aerial refueling, and for space debris clearance operations. The theory behind stereo image depth calculation is explained and then synthetic pixel data is manufactured in order to determine a 95% confidence interval on depth under two camera baseline conditions. A Gaussian pixel error is add to simulate Harris corner detection error. A disparity of the order of 10 pixels or less produces more than 1 cm difference between expected and actual depth for the stereo camera bases examined. For a 1-pixel disparity the difference is of the order of 50%. Future research is discussed.","PeriodicalId":392498,"journal":{"name":"2019 24th International Conference on Methods and Models in Automation and Robotics (MMAR)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 24th International Conference on Methods and Models in Automation and Robotics (MMAR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMAR.2019.8864723","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

This paper examines the effect on achievable depth accuracy of a stereo vision system as the baseline between the two camera sensors changes. This is critical for Unmanned Aerial Vehicle navigation or UAV aerial refueling, and for space debris clearance operations. The theory behind stereo image depth calculation is explained and then synthetic pixel data is manufactured in order to determine a 95% confidence interval on depth under two camera baseline conditions. A Gaussian pixel error is add to simulate Harris corner detection error. A disparity of the order of 10 pixels or less produces more than 1 cm difference between expected and actual depth for the stereo camera bases examined. For a 1-pixel disparity the difference is of the order of 50%. Future research is discussed.
可实现立体视觉深度精度与改变相机基线
本文研究了两个相机传感器之间的基线变化对立体视觉系统可达深度精度的影响。这对于无人机导航或无人机空中加油以及空间碎片清理行动至关重要。解释了立体图像深度计算背后的理论,然后制造合成像素数据,以确定两个相机基线条件下深度的95%置信区间。加入高斯像素误差来模拟哈里斯角点检测误差。对于所检查的立体相机底座,10像素或更小的数量级的差异会在预期深度和实际深度之间产生超过1厘米的差异。对于1像素的视差,差异约为50%。展望了未来的研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信